CharSPBench: An Interaction-Aware Micro-Architecture Characterization Framework for Smartphone Benchmarks

Mobile application workloads are inherently driven by user interactions and are characterized by short execution phases and frequent behavioral changes. These properties make it difficult for traditional micro-architecture analysis approaches, which typically assume stable execution behavior, to accurately capture performance bottlenecks in realistic mobile scenarios. To address this challenge, this paper presents CharSPBench, an interaction-aware micro-architecture characterization framework for analyzing mobile benchmarks under representative user interaction scenarios. CharSPBench organizes micro-architecture performance events in a structured and semantically consistent manner. It further enables systematic attribution of performance bottlenecks across different interaction conditions. The framework further supports intensity-based workload analysis to identify workload tendencies, such as memory-intensive and frontend-bound behaviors, under interaction-driven execution. Using the proposed framework, 126 micro-architecture performance events are systematically organized. This process leads to the identification of 19 key, semantically non-redundant features, further grouped into five major micro-architecture subsystems. Based on this structured representation, eight representative interaction-dependent micro-architecture insights are extracted to characterize performance behavior across mobile benchmarks. These quantitative results demonstrate that CharSPBench complements existing micro-architecture analysis techniques and provides practical support for interaction-aware benchmark design and mobile processor performance evaluation.